1

Chinese Political and Economic Governance System and the Imbalance

between Consumption and Investment

Julan Du

Department of Economics

Chinese University of Hong Kong

Hongsheng Fang

College of Economics

Zhejiang University, China

Xiangrong Jin

College of Economics

Zhejiang University, China

Abstract

The Chinese government has been pursuing economic growth under the guidance of

“growth is a hard principle”. In the context of the Chinese political and economic

governance system, local governments have employed the overtaking strategy

(placing primary emphasis on the development of capital and technology-intensive

industries) and the real estate development strategy to push for economic growth and

fiscal revenue growth. This led to a repressed labor share and an elevated capital and

government share in primary and secondary income distribution structure. Using the

empirical strategy of Acemoglu et al. (2003), we confirm that the development

strategies have shaped an imbalanced consumption-investment structure through

primary and secondary income distribution structure as well as other channels. It

suggests that the Chinese government will be able to accomplish China’s transition

from an investment-led growth model to a consumption-based growth model only if it

modifies its political and economic governance system and removes the distortions in

development strategies.

Keywords: Overtaking strategy; Real estate development strategy, Biased income

distribution structure；Consumption-investment imbalances.

JEL classification: E62, E65, H20, H77.

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1. Introduction

China’s growing current account surplus has been a hot topic for both economic

analyses and policy debate (Blanchard, 2005; Yu, 2007; Goldstein and Lady, 2008). It

has been widely regarded as one major factor contributing to global economy

imbalances and the global financial crisis triggered by the U.S. subprime credit crisis

(Kawai and Zhai, 2009). In this view, China’s large current surplus and investment in

the U.S. Treasury bonds helped lower the U.S. interest rates and caused property and

equity market bubbles in the U.S., which then led to the subprime credit crisis and the

global financial crisis (Krugman, 2009, 2010). Thus, the rebalancing of the U.S. and

China bilateral trade balances is considered a prerequisite for the sustained global

recovery (Goldstein, 2010).

This undertaking, however, requires an understanding of what are the

fundamental reasons for China’s growing current account surplus. In our view,

China’s external imbalances coexist with its internal imbalances, both of which stem

from, to a large extent, the “growth first strategy” of the Chinese government and the

resultant income distribution structure favoring capital and government instead of

labor. It is widely documented that the ruling Chinese Communist Party (CCP) and

the public reached an implicit social contract in which the government promised to

deliver rapid economic growth in return for the acceptance of the public of an

authoritarian political regime. To achieve the goal of promoting economic growth, the

CCP has established a regionally decentralized authoritarian regime characterized by

political centralization and economic decentralization. The central leadership employs

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promotion tournament and tax sharing system to motivate regional bureaucrats to

pursue rapid local economic growth. Naturally, regional bureaucrats adopt the

overtaking strategy, i.e., to place primary emphasis on the development of capital and

technology-intensive industries, and the real estate development strategy, to stimulate

local economic growth. As a consequence, these strategies led to an income

distribution structure biased toward capital and government and against labor. A

repressed labor share and an elevated capital and government share would discourage

consumption and encourage savings and investment, resulting in a salient feature of

internal macroeconomic imbalances, that is, the consumption-investment structure

imbalances. Moreover, this internal imbalance coexists with external imbalance.

Overinvestment and underconsumption enlarged the gap between aggregate supply

and effective demand (Lin et al., 2010; Wang and Fan, 2009). The insufficiency of

domestic consumption demand pushed firms to export their products to overseas

markets so that production surplus has turned into trade surplus. Hence, the

phenomena of the overinvestment and underconsumption, high return on capital (Bai

et al., 2006), high enterprise and government savings in China, and high trade surplus

are endogenous to the overtaking strategy and the real estate market development

strategy generated by the Chinese political and economic governance system. This in

turn helps us solve some puzzles about the Chinese economic structure adjustment

and global economy rebalancing, i.e., why the Chinese central government’s efforts to

increase domestic household consumption failed miserably and why it is so difficult

for China to transform its model of economic growth from an investment-led one to a

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consumption-based one.

Using province-level panel data set over the period 1996-2007, we show that the

proxy indicators of the overtaking strategy and the real estate development strategy

have resulted in an imbalanced consumption-investment structure. One important

channel is the biased income distribution structure that favors capital and government.

In addition, the government’s development strategies affect the consumption-

investment structure through other channels. Our study points out that the Chinese

political and economic governance system, which was widely acclaimed as the

institutional foundation for China’s economic miracle in the past three decades, has

also generated serious distortions in primary and secondary income distribution

structure, which is a major source of income distribution inequality and social

tensions. This directly contributes to underconsumption and overinvestment, and

generates enormous difficulties for China’s transition from an investment-led growth

model to a consumption-based growth model in the current China.

In our analysis, we also take into consideration how the consumption–investment

structure evolves with the level of economic development and demographic structure.

We expect to observe a U-shaped relationship between consumption ratio and GDP

per capita and an inverted U-shaped relationship between investment ratio and real

GDP per capita, and a U-shaped relationship between consumption ratio and the aged

dependency ratio and an inverted U-shaped relationship between investment ratio and

the aged dependency ratio. Our analysis confirms this prediction.

This paper makes the following contributions to the literature. First, we provide a

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coherent framework for understanding both the internal imbalance, i.e., the

unbalanced consumption-investment structure, and the external imbalance, i.e., the

growing trade surplus, in China.

Second, following the empirical strategy of Acemoglu et al. (2003), we confirm

that the Chinese political and economic governance system has shaped an imbalanced

consumption-investment structure through the biased income distribution structure as

well as other channels. It suggests that getting the incentives in the governance system

right and removing the distortions in the primary income distribution structure are

necessary to achieving a consumption-based growth model in China.

Third, this study enriches the literature on the macroeconomic imbalances of

China by emphasizing their institutional foundations. A growing literature has

addressed the reasons for China’s external macroeconomic imbalances, which may be

broadly grouped into six categories: measurement errors (Zhang, 2009), savings and

investment gap (Feenstra et al., 1999; Bernanke, 2007; Chinn and Ito, 2007; Zhou,

2009; Woo, 2006), industrial relocation (Lardy, 1994, 2006; Greenspan, 2005; Li and

Li, 2006), by-product of policies promoting growth (Corden, 2009), exchange rate

distortion (Krugman, 2009, 2010; Goldstein, 2010) and imbalances between

consumption and investment (Blanchard, 2005; Lin et al., 2010; Lin, 2011; Huang and

Tao, 2010; Huang, 2010a; Huang, 2010b; Huang and Wang, 2010; Wang and Fan,

2009; Fang and Jin, 2010). Though each category provides valuable insights, no much

work has linked explicitly the Chinese political and economic governance system

with China’s macroeconomic imbalances.

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The rest of this paper is organized as follows. Section 2 develops our hypotheses

in detail. Section 3 introduces data and lays out the econometric models and

estimation methods. Section 4 discusses the results of empirical tests of the

abovementioned hypotheses. The final section concludes and offers some important

policy implications.

2. Hypothesis Development

2.1. The Overtaking Strategy and Consumption-Investment Imbalances

It is observed that there is a substantial shift in development policies pursued by

local governments around the mid-1990s (Cai, 2009; Bergsten et al., 2009; Rodrik,

2006, 2010；Anderson，2008). Before then, local governments promoted labor-

intensive industries, which is consistent with China’s comparative advantage in the

global economy. Afterwards, local governments pursued an overtaking development

strategy by promoting capital and technology-intensive industries, which is deviant

from China’s comparative advantage.

This transition in development strategy coincided well with the formulation of

the growth-first strategy of the central leadership. The late Chinese paramount leader,

Deng Xiaoping, had a tour of South China and gave a series of speeches in early

1992. He adopted a pragmatic approach in emphasizing that the primary task of

Chinese government was to pursue economic growth, which was a hard principle.

Clearly, the Chinese leadership realized that the CCP did not have procedural

legitimacy in keeping the monopoly of political power so that it must deliver superior

performance in economic growth to win performance legitimacy (Jefferson and

Zhang, 2008). Otherwise, the regime could hardly be maintained.

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A regionally decentralized authoritarian system has laid institutional foundation

for the fulfillment of the growth-first strategy. China is characterized by highly

centralized political and personnel control at the national level, and a decentralized

administrative and economic system at the provincial and local levels (see, e.g.,

Blanchard and Shleifer, 2001；; Clarke, Murrell, and Whiting, 2008; Xu, 2011). This

allows the central government to motivate local bureaucrats to achieve high growth

targets through promotion tournament. It is documented in the literature that, in order

to achieve the goal of the growth-first strategy, the political appointments and

promotions of regional and local bureaucrats were based on their performance in

promoting economic growth and their performance relative to that of their immediate

predecessors (Tsui and Wang，2004; Li and Zhou, 2005; Chen et al., 2005). One

important method of accelerating local GDP growth is to adopt an industrial policy

that places primary emphasis on the development of capital and technology-intensive

industries instead of labor-intensive ones (Peneder, 2003; Lin and Chang, 2009;

Rodrik, 2006, 2010; Hausmann et al., 2007). In the traditional neo-classical growth

model, the accumulation of capital and capital deepening play a vital role in

promoting output growth, which is largely verified by subsequent empirical studies

(see, e.g., Mankiw, Romer and Weil, 1992). Recently, in examining the world growth

experience, Jorgensen and Vu (2009, 2010) show that approximately 40-50% of world

growth can be attributed to the accumulation and deployment of capital. Surprisingly,

the use of labor input and productivity growth contribute only 25-33% and 20-35%

respectively. Hence, the growth experience of the world economy has testified to the

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importance of capital and technology-intensive industries in raising GDP growth.

Thus, it is not surprising that local bureaucrats with career concerns and facing the

pressure of promotion tournament gave priority to the development of capital and

technology-intensive industries.

At the same time, the tax sharing system reform also strengthened the incentives

of local bureaucrats to promote capital and technology-intensive industries. On the

one hand, the central government has centralized tax revenues to a large extent

through the tax sharing reform, but at the same time, the responsibilities of local

governments for local public expenditure largely remained intact. This generated

mounting pressures on the fiscal capacity of local governments, which forced local

bureaucrats to explore new avenues for raising tax revenues. Local governments

understandably strove to develop capital and technology-intensive industries that

could swiftly raise local GDP growth and tax revenue growth. On the other hand, the

sharing scheme of production-based value added taxes (VAT) is the cornerstone of the

tax sharing reform between the central and local governments. The production-based

VAT is divided between the central and local governments at a ratio of 75:25 as a

basis rate. If the local government collects an amount of value-added taxes more than

the contracted target, the division between the central and local governments will

follow the ratio of 52.5:47.5, which is much more favorable to the local government

due to the tax rebate scheme. These taxation schemes further motivate local

governments to develop capital and technology-intensive industries because these

industries typically require substantial fixed asset investments that could forcefully

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generate GDP growth and VAT revenues.

In a nutshell, under the guidance of the growth-first development strategy, the

regionally decentralized authoritarian system in China has generated bureaucratic

promotion tournament on the basis of local economic growth record, which

encouraged local bureaucrats to promote tirelessly the development of capital and

technology-intensive industries. This incentive is reinforced by the tax-sharing system

reform that started in 1994. They form the institutional foundations for the local

development strategy that gives priority to capital and technology-intensive industries.

Only by pushing hard those capital and technology-intensive industries are local

bureaucrats able to achieve high growth in local GDP and local tax revenues, which in

turn enhance the promotion prospects of local bureaucrats and relieve local fiscal

expenditure burden.

As shown in Figure 1, the proportion of asset value of heavy industry in the total

asset value of industries has remained above 65% since 1994 and displayed an

upward trend. In 1994, the ratio was around 65%, but it rose to 71% in 2003 and

nearly 77% in 2009. The proportion of annual average net value of fixed assets of

heavy industry in that of all industries exhibited a similar pattern.

The capital and technology-intensive industries have also contributed a

substantial and an increasing share in industrial value added. Figure 2 shows that the

ratio of value added of heavy industry to total industrial value added in China has

remained above 60% in almost all years since 1994, and it reached nearly 66% in

2003, and 70% in 2007.

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Consequently, it is natural for the capital and technology-intensive industries to

play a leading role in generating tax revenues. Figure 3 illustrates that the value added

tax payable of heavy industry accounts for a proportion of 65%-75% in the period

1994-2009. Similarly, the proportion of total tax payable of heavy industry in that of

all industries has remained above 56% in the period 1994-2009, and exhibited a rising

trend since 1998, reaching 68% in 2009.

The overtaking strategy consists of a series of industrial policies to support the

development of capital and technology-intensive industries. This strategy is expected

to raise the share of budgetary revenues and capital income in the national income and

reduce that of labor income. On the one hand, the overtaking strategy raises the

amount of capital employed and the expected return on capital so as to increase the

share of capital income in GDP. According to the neo-classical economic theory, the

share of labor income is affected by the capital-output ratio and the elasticity of

substitution between labor and capital in the production function. When the

substitution elasticity between capital and labor is larger than one, an increase in the

capital-output ratio is accompanied by a decrease in labor’s share in income. In other

words, when one unit increment in capital use crowds out more than one unit of labor,

the income share of labor would decline (Bentolila and Saint-Paul, 2003). It is widely

documented in the literature that capital and unskilled labor are substitutes whereas

capital and skilled labor are typically complements (Schneider, 2011). Under China’s

overtaking strategy, the industrial development biased toward capital and technology-

intensive industries typically means a large degree of substitution of capital for

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unskilled labor. Recent empirical studies find that the elasticity of substitution

between labor and capital was greater than 1 in 28 industries in the period 1996-99

and in 20 industries in the period 2000-5 (Yuan and Li, 2008). Therefore, the

overtaking strategy might well result in a declining labor share and a rising capital

share in income by encouraging resources to flow to capital and technology-intensive

industries.

In addition to increasing capital employment, the overtaking strategy also raises

the return on capital. (1) Local governments took a wide range of measures to lower

the costs of doing business. They provide preferential tax treatment, repress land use

fees, offer fiscal subsidies, and overlook environmental protections to provide

favorable treatment for investors. One striking aspect is that local governments were

enthusiastic with establishing economic and/or high-tech industry development zones,

and granted the enterprises engaged in capital and technology-intensive industries

therein with many favorable treatments. (2) Local governments spared no effort to

improve infrastructure facilities. This could attract foreign direct investment (FDI)

(Zhang et al., 2007), and could directly create demand for the products of capital and

technology-intensive industries and boost local GDP growth. Consequently, it is

documented in the literature that the structure of local government expenditure is

highly biased toward infrastructure investment rather than those related to social

welfare, which has weakened the social safety net for local residents and intensified

households’ motive for precautionary savings (Fu and Zhang, 2007; Nitikin et al.,

2011). (3) Moreover, China’s state-dominated financial system with financial

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repression helped lower the cost of capital. The tight restriction on capital outflow and

the lack of alternative investment instruments enable household savings deposited in

banks to keep rising, leading to an increasing supply of capital. The interest rate

regulations kept costs of loans at a low level. These factors pushed down costs of

capital (Huang, 2010), and facilitated local governments to provide low-cost financing

from the state-controlled financial system to investors. (4) In addition, local

bureaucrats often helped maintain monopoly positions for the firms in local markets

through market segmentation. By restricting the flow of products from other regions,

local governments allowed local enterprises to retain market monopoly power so as to

achieve a high rate of return on investment (Lin and Liu, 2004). These actions, when

combined together, have stimulated the development of capital and technology-

intensive industries by raising the return on capital and the share of capital income in

value added ①

On the other hand, the overtaking strategy steered resources away from labor-

intensive industries towards capital-intensive ones, repressing the expansion of

demand for labor and employment. Moreover, local governments did not make

sufficient efforts to uphold labor rights. To push for GDP growth, local governments

went all out to attract investment. When conflicts between capital and labor arise,

local governments give priority to protecting the interests of capital while largely

overlooking workers’ rights (Lu and Gao, 2010). Since the overtaking strategy

facilitates capital and technology-intensive industries to raise funds from the state-

Rodrik(2010) expressed similar viewpoints.

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dominated financial system, medium and small-sized enterprises in labor-intensive

industries typically found it hard to obtain loans. Their investment relied heavily on

retained profits. To enlarge retained earnings, those enterprises typically squeezed

labor compensation and lengthened working hours. At the same time, the fierce

competition in labor-intensive industries has further forced enterprises to keep a low

wage rate and fringe benefits for labor. These factors slowed down the expansion of

labor force and the rise in wage rate and fringe benefits for workers, resulting in an

increasing capital share and a diminishing labor share in labor-intensive industries.

Therefore, we can infer that the overtaking strategy will increase capital share and

reduce labor share in GDP.

The overtaking strategy is also expected to raise the share of government

income. Firstly, capital and technology-intensive industries often have higher value

added from which governments can collect a larger amount of value added taxes.

Secondly, taxation capacity variation across industries also matters. Value added taxes

are the major source of government income from primary income distribution. It is

easier for tax authority to collect taxes from firms operating in capital- and

technology-intensive industries than those in labor-intensive industries. Capital- and

technology-intensive industries often have a higher proportion of large firms than do

labor-intensive industries. It is widely documented in the literature that in developing

countries large firms are typically more visible and are subject to more intensive

oversight of governments than do small firms. When the governments have relatively

weak taxation capacity and limited resources for tax enforcement, taxes and

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regulations are often enforced only among those large firms (Tybout, 2000). Hence,

firms in capital- and technology-intensive industries are less likely to evade tax

payment, and the bias of industrial development toward these firms would result in a

larger government share in primary income distribution. Thirdly, the design of the

value added tax system creates distortions. By 2008, the production-based value

added tax does not give deduction to the previous tax payment for fixed asset

purchases so that there exists double taxation of fixed asset depreciations (Guo and

Lv, 2010). For capital and technology-intensive industries, this double taxation is

much more serious because of the larger purchase value of fixed assets, and

consequently government income share is also higher. Hence, preferential

development of capital and technology-intensive industries is expected to raise the

government share of income.

So far, we have demonstrated that the overtaking strategy would result in a

primary income distribution structure biased toward capital and government and

against labor. However, it is noteworthy that the overtaking strategy would also result

in a secondary income distribution structure biased toward capital and government

and against labor. The secondary income distribution structure results from the

redistribution efforts of governments through tax collection and fiscal transfers.

According to Lv and Guo (2012), the secondary income distribution structure differs

from the primary one in China mainly because of the corporate income taxes levied

on capital, the social insurance payments collected from labor, and government

transfers to labor. In the context of our framework, the overtaking strategy raises

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income accruing to capital, which in turn increases the share of corporate income tax

and that of government income in GDP in the secondary income distribution structure.

At the same time, local government expenditure under the overtaking strategy puts a

much larger weight on productive investment such as infrastructure investment than

on social welfare improvement. Moreover, the demographic dividends, i.e., the

decline in population growth rate coexists with a larger size of working age

population than that of aged population, enable social insurance payments collected

from labor to exceed that withdrawn by labor. As a result, government transfers to

labor and social welfare expenditure share in GDP remain small (Fu and Zhang,

2007). Thus, we expect that, compared with the primary income distribution structure,

the overtaking strategy will increase the government share and reduce the labor share

in national income after redistribution. Across provinces, those pursuing the

overtaking strategy more intensively would have a particularly larger government

share and lower labor share in income. On the other hand, relative to the primary

income distribution structure, corporate income tax might reduce the share of capital

in national income in the secondary income distribution structure, which is confirmed

by Lv and Giuo (2012). Nonetheless, because corporate income tax is a type of

proportional tax, it would not change the relative size of capital income share between

different provinces pursuing the overtaking strategy. Those provinces pursuing the

overtaking strategy more intensively are expected to have a higher capital share in the

secondary income distribution structure than those less intensively.

Consequently, we expect that the government’s redistribution would not benefit

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much the labor and the cross-province variation in the secondary income distribution

structure would be fairly consistent with that in the primary income distribution.

Figures 4-6 present the scatterplots of province-level annual shares of labor, capital

and government in the primary income distribution structure (on the horizontal axis)

and the secondary income distribution structure (on the vertical axis) in the sample

period. Quite strikingly, the labor income share is highly consistent before and after

redistribution. The capital income share and the government income share are also

quite consistent before and after government income redistribution, although

occasionally the capital share is slightly lower and the government share is slightly

higher in the post-redistribution period.

The largely same pattern changes in the primary and secondary income

distribution structure are expected to contribute to an imbalanced consumption-

investment structure, that is, the ratio of consumption to national income would be

lowered and that of investment to national income be raised. On the one hand, a

declining labor share in GDP would reduce the share of household disposable income

in GDP because labor income constitutes the most basic form of household disposable

income for most households. Recent studies (see, e.g., Aziz and Cui, 2007; Guo and

N’Diaye, 2010) have shown that low disposable household income is a principal

culprit of low consumption in the Chinese economy. On the other hand, capital

income typically has a lower propensity to consume than does labor income. In the

context of the overtaking strategy, governments in China prefer productive investment

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to government consumption, especially social welfare provision. ②

Hence, a higher

share of government and capital income in GDP is expected to be associated with a

higher ratio of investment to GDP and a lower ratio of consumption to GDP.

Hypothesis 1: The regionally decentralized authoritarian regime in China generates

an overtaking strategy placing primary emphasis on the development of the capital

and technology-intensive industries, which leads to primary and secondary income

distribution structure biased toward capital and government and against labor.,

weakens the social safety net, softens budget constraint, and results in an imbalanced

consumption-investment structure.

2.2. The Real Estate Development Strategy and Consumption-Investment

Imbalances

Besides the overtaking strategy, the Chinese political and economic governance

system has given rise to real estate development scheme as another strategy for local

governments to achieve growth in GDP and fiscal revenues. Under the tax-sharing

reform scheme, local governments are given land lease revenues as extra-budgetary

funds to alleviate their fiscal burden (Nitikin et al.,2011; Liu and Sun; Su et al.,2012).

As a natural result, local governments have vehemently pursued the development of

the real estate sector. Property market development and the increase in housing

market prices can help land lease generate maximum fiscal revenues (Liu and Sun),

②

However, it should be emphasized that although a rising share of tax revenues in national income has spurred their tendency to expand investment, local governments that adopt the overtaking strategy will not be constrained by the amount of budgetary revenue. In order to increase investment, they will seek funds from land transfer revenue-based extra-budgetary revenue and land-based mortgage loans (Nitikin et al., 2011).

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which provides funds for local governments to pursue various political and economic

objectives，especially government-initiated investment in infrastructure, productive

activities, etc. Property market development can also stimulate the growth of the

related upstream and downstream capital-intensive industries, which gives further

impetus to local GDP growth and fiscal revenue growth. Consequently, the real estate

development strategy directly contributes to the boom in investment, which reinforces

the imbalanced consumption-investment structure. Furthermore, like the overtaking

strategy, real estate development strategy is also expected to generate primary and

secondary income distribution structure biased toward capital and government and

against labor, which would contribute to a distorted consumption-investment structure

characterized by underconsumption and overinvestment. It is noteworthy that local

governments’ land lease system provides an important institutional support to real

estate development strategy. By keeping monopoly power over the primary market for

land, local governments have strong incentives and discretion to raise land prices by

controlling the size of land supply through the land reserve system. Because real

estate assets are relatively scarce, illiquid, and of fixed supply in the short run, the

increase in land prices was in turn transmitted to housing prices and the burden was

borne by house purchasers (Su et al.,2012).

Local governments have adopted various measures to boost real estate market

development and raise housing prices. In addition to fine-tuning land supply, local

governments stimulated the household demand for housing by phasing out public

housing provision scheme in 1998, accelerating the urbanization process, adjusting

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taxation strategies, forming collusion with property developers and banks in pushing

up housing prices, etc. The dramatic rise in housing prices has encouraged households

to form expectations for future increases (Liu and Sun), which induced large amounts

of capital to flow into the property market, leading to a spiral increase in housing

prices and the expansion of capital-intensive industries. This kind of expectation not

only stimulated speculative investment demand for property, but also strengthened the

propensity of average households to save for the purpose of property purchase, which

further caused consumption to shrink and investment to expand. Hence, we have the

following hypothesis.

Hypothesis 2: The regionally decentralized authoritarian regime in China generates

real estate development strategy, which leads to primary and secondary income

distribution structure biased toward capital and government and against labor ,

stimulates speculative investment demand through expectations of surging property

prices, strengthens households’ motive for precautionary savings, and generates huge

land lease revenues,and therefore, contribute to an imbalanced consumption-

investment structure.

In summary, Hypotheses 1-2 argue that the overtaking strategy and the real estate

market development strategy generated by the Chinese political and economic

governance system are the fundamental institutional foundations for the imbalanced

consumption-investment structure, i.e., under-consumption and over-investment.

Meanwhile, albeit the existence of other mechanisms, the distorted primary and

secondary income distribution structure reflected in a repressed share of labor income

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and an elevated share of capital and government income in national income serve as a

major mediating channel for the two development strategies to shape the

consumption-investment structure.

2.3. Economic Structural Transformation, Demographic Characteristics, and the

Consumption-Investment Structure

In addition to the institutional reasons, consumption and investment structure

may evolve with economic structure transformation following economic

development③. Generally, labor share in value added is smaller in the secondary

industry than in other industries. We therefore expect that labor share will decline

when an economy transforms from an agriculture-based one to a secondary industry-

based one, but will rise when the economy moves toward a tertiary-industry -based

one. Thus, labor share in GDP is expected to show a U-shaped relationship with real

GDP per capita (Chenery, 1982; Li et al., 2009). Similarly, because capital and

government shares are higher in the secondary industry than in other industries, it is

not difficult to infer an inverted U-shaped relationship between both capital and

government shares and real GDP per capita. Since labor share is of utmost importance

to household consumption share in GDP, we expect that consumption rate will display

a U-shaped relationship while investment rate an inverted U-shaped relationship with

③

Some earlier studies (Rostow,1960;Chenery and Syrquin,1975) argued that at a lower

development level, the share of the secondary industry value added in GDP is smaller than that of

primary industry, resulting in a lower social organic constitution of capital and therefore a lower

investment rate. Then, the investment rate will rise when an economy transforms from a primary

industry-based one to a secondary industry-based one, but will decline when the economy moves

toward a tertiary-industry-based one. Here, we give a different explanation for the mechanisms

behind the effects of structural transformation.

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the real GDP per capita (economic development stages).

Hypothesis 3: Ceteris paribus, the consumption rate and investment rate display a U-

shaped and an inverted U-shaped relationship with real GDP per capita, respectively.

It is noteworthy that besides Hypotheses 1-2, Hypothesis 3 also implies that

economic structure transformation might shape the consumption-investment structure

through the primary income distribution structure, that is, economic structure shapes

the relative shares of labor, capital and government in national income so as to affect

the consumption-investment structure.

Moreover, consumption-investment structure is associated with the demographic

characteristics. When the dependency ratio, especially the old-age dependency ratio,

is small, workers have less need for savings to support the elderly, which would

expand consumption. When the old-age dependency ratio rises, the working

population faces a higher burden and tends to consume less and save more. Since at

this stage the working population still accounts for a large share of the whole

population, the decreasing propensity to consume would lead to a shrinking

consumption rate and a rising savings rate. When the old-age dependency ratio

exceeds some critical level, the society will enter a phase of dissaving, i.e., the

consumption (savings) rate of households would increase (decrease).

Hypothesis 4:Ceteris paribus, the consumption rate and investment rate display a U-

shaped and an inverted U-shaped relationship with the old-age dependency ratio,

respectively.

3. Data and Methodology

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3.1. Model Specifications

To test Hypotheses 1-4, we conduct province-level panel data regressions. Our

analysis consists of several steps. Firstly, we examine the impacts of the overtaking

strategy and the real estate development strategy as well as other factors on the

consumption-investment structure. We carry out regressions of the following three

specifications (Equations 1-3).

Consumption ratioit = 1 Overtaking Strategyit + 2 Real Estate Development Strategyit

+ 3 GDPPCit+ 4 GDPPC-sqit+ 5 Old Age Dependency Ratio+ 6 Old Age

Dependency Ratio-sqit + Controlit+ i + it (1)

Investment ratioit = 1 Overtaking Strategyit + 2 Real Estate Development Strategyit +

3 GDPPCit+ 4 GDPPC-sqit+ 5 Old Age Dependency Ratio+ 6 Old Age

Dependency Ratio-sqit + Controlit + i + it (2)

Consumption ratio/Investment ratioit = 1 Overtaking Strategyit + 2 Real Estate

Development Strategyit + 3 GDPPCit+ 4 GDPPC-sqit+ 5 Old Age Dependency

Ratio+ 6 Old Age Dependency Ratio-sqit + Controlit + i + it (3)

Here we gauge the consumption-investment structure by three indicators.

Consumption ratio is the proportion of household consumption expenditure in GDP;

Investment ratio is the fraction of gross fixed capital formation in GDP. To better

capture the relative strength of consumption vis-à-vis investment, we also include the

ratio of consumption to investment.

Secondly, we investigate the impacts of the overtaking strategy and the real

estate development strategy, along with other factors, upon income distribution

23

structure (Equations (4)-(7)).

Labor Income Shareit = 1 Overtaking Strategyit + 2 Real Estate Development

Strategyit + 3 GDPPC it+ 4 GDPPC-sqit+ Controlit + i + it (4)

Capital Income Shareit = 1 Overtaking Strategyit + 2 Real Estate Development

Strategyit + 3 GDPPCit+ 4 GDPPC-sq it+ Controlit + i + it (5)

Gov’t Income Shareit = 1 Overtaking Strategyit + 2 Real Estate Development

Strategyit + 3 GDPPCit+ 4 GDPPC-sq it + Controlit + i + it (6)

Labor Income Share/ (Capital Income Share+ Gov’t Income Share) it = 1 Overtaking

Strategyit + 2 Real Estate Development Strategyit + 3 GDPPCit+ 4 GDPPC-sqit +

Controlit + i + it (7)

Here Labor income share is the fraction of GDP serving as labor compensation;

Capital income share is the ratio of the sum of operating surplus and fixed asset

depreciation to GDP; and Government income share is the proportion of net

production tax in GDP. To capture the relative strength of labor income share, which

is instrumental to the determination of household consumption, we also include a

dependent variable of the ratio of labor income share to the share of capital and

government income.

Finally, we test whether the government strategies have shaped the consumption-

investment structure through the income distribution structure. To do so, we follow

the strategy of Acemoglu et al. (2003) to conduct a series of regression analyses. We

first put Labor Income Share/ (Capital Income Share+ Gov’t Income Share) into

regression equation (3). Then, to assess whether the overtaking strategy and real estate

24

market development strategy affect the consumption-investment structure via income

distribution structure, we adopt the following criteria:

1. If the overtaking strategy and real estate market development strategy lose

statistical significance or their statistical significance and/or the magnitude of the

estimated coefficients have dropped substantially, while the income distribution

structure variable is statistically significant, we can regard primary income

distribution structure as a primary mediating channel for the impact of the government

strategies on the consumption-investment structure. Since the primary income

distribution structure is the main mediating channel, these results would suggest that

getting primary income distribution structure right is likely to be an important policy

priority.

2. If the variable of income distribution structure is not statistically significant, it is

not regarded as one of the channels linking government strategies to an imbalanced

consumption-investment structure. In this case, the effect of government strategies on

the consumption-investment structure is likely to be working through a variety of

other channels.

3. If both income distribution structure and the overtaking strategy and real estate

market development strategy are statistically significant, and the statistical

significance and magnitude of the latter estimated coefficients have not dropped

substantially, we can conclude that primary income distribution structure is only one

important channel, but it is not the primary mediating channel via which government

strategies translate into an imbalanced consumption-investment structure.

25

In panel data regression estimation based on Equations (1)-(7) above, we use the

method of Driscoll and Kraay (1998) that deals with cross-sectional dependence. If

cross-sectional dependence exists but is not addressed, regressions would result in

misleading conclusions. Compared with the feasible generalized least squares (FGLS)

method, this method could more effectively deal with the problems of autocorrelation,

heteroskedasticity, and cross-sectional correlation in small samples where the number

of cross-section units is larger than that of time periods.

3.2. Data and Variables

Our empirical analysis is mainly based on panel data from 27 provinces in China

in the period 1996-2007. Because of lack of consistent data in the period covered, our

sample does not include four province-level administrative regions, i.e., Chongqing,

Hainan, Sichuan, and Tibet. Detailed data sources are reported in Appendix A and

summary statistics of all key variables are provided in Table 1.

We use three alternative indicators as proxy measures of the intensity of local

governments’ pursuit of an overtaking strategy. The first one is the technology choice

index proposed by Lin (2009), TCI. It is defined as TCI=(AVI/LI)/(GDP/L) ,where

AVI is the value added of the high-technology industries, GDP is the total added

value, LI is number of employees in high-technology industry and L is the total

number of employees in the province. If a government adopts an overtaking strategy

to promote capital and technology-intensive industries, the TCI in this province is

expected to be larger than otherwise. Under an overtaking strategy, the local

government typically granted some monopoly power in output market for those

enterprises engaged in capital and technology-intensive industries. At the same time,

local governments often provided subsidies and cheap loans for them to lower their

26

investment and operational costs. These policies tend to raise AVI in the TCI indicator.

On the contrary, these capital and technology-intensive industries can absorb a

relatively small amount of labor (LI), which, coupled with the above factor, helps

raise the value of the TCI indicator. Hence, when holding income and other conditions

constant, a higher value of the TCI index (named as variable the overtaking strategy1)

corresponds to a more intensive pursuit of the overtaking strategy.

Based on Hypothesis 1, we expect that the estimated coefficients of the overtaking

strategy1 are statistically significant and negative in Equations (1) , (3), (4) and (7),

and statistically significant and positive in Equations (2), (5) and (6).

Nevertheless, this TCI index has its weaknesses. It is built upon the basis of

industrial structure, which might be affected by the natural evolution process of

structural transformation in economic development as well as local government

policies. To capture more powerfully the intention of local governments to pursue the

overtaking strategy, we construct two indices based on local economic and

technological development zones as proxy variables for the overtaking strategy. They

are the logarithm of the number of local development zones (the overtaking strategy2 )

and the logarithm of the land area of local development zones (the overtaking

strategy3

), respectively, which are taken from the Directory of Approved Development

Zones in China (2006) . Table 2 lists the number and land area of the development

zones officially approved by either the central government (the State Council) or

provincial governments. It shows that the growth rate of development zones was

relatively low in the first eight years.④

Since Deng’s remarks that re-launched

④

The first development zone was established in Guangzhou in 1984 with approval obtained directly from the State Council. The practice was originally to emulate the experience of export processing zones in other developing countries. To attract foreign investment and facilitate the import of foreign technology as well as equipment, a special land area is designated, where tax concession and other

27

economic reforms in 1992, there was a wave of the establishment of development

zones. Under the Chinese regional decentralized authoritarian regime, local

governments have very strong incentives to seek the approval of the central

government (the State Council) or provincial governments for their plans of setting up

development zones ⑤

. By the end of 2006, the total number and land area of the

development zones approved by the State Council and provincial governments were

1568 and 999,350 hectares, respectively. Among them, the number of national

development zones and provincial-level zones were 222 (14%) and 1,346 (86%),

respectively; the land area occupied by national development zones and provincial-

level zones were 236,760 (24%) and 762,590 hectares (76%), respectively.

The inventory of official development zones has included information on the

nature of these zones and their distribution. This is listed in Table 3. Among the five

main categories of national development zones, hi-tech industrial development zones

(HIDZs) accounted for over 40 percent of the land areas covered and economic and

technological development zones (ETDZs) 27 percent; export processing zones

(EPZs) accounted for over 26 percent of the total in number, HIDZs 24 percent, and

ETDZs 22 percent. By comparison, those approved by provincial governments were

dominated by economic development zones (EDZs), which took nearly 90 percent of

the land area designated. Considering that these development zones have set higher

technology and capital requirements for entrant firms, we can conclude that they

reflect the policy initiatives of local governments in accelerating the development of

preferential treatments are offered to foreign investors(see Lin, G(2009) for details). ⑤In 1993, the State Council formally conducted two level approve system on the establishment of development zones. i.e., the national development zones approved by the State Council, while the provincial development zones approved by provincial governments.

28

capital and technology-intensive industries.

We use the ratio of land lease (land transfer) revenues to budgetary fiscal revenue

as a proxy for local governments’ efforts to develop local real estate market. As

discussed above, land lease revenues are the major source of extra-budgetary revenues

for local governments. To acquire land, local governments typically exercise

administrative power to appropriate land use rights at an extremely low acquisition

price from farmers. Afterwards, by going through the land consolidation and

reorganization process, local governments could sell the land use rights at a much

higher price, from which local government reap tremendous land lease revenues.

Examining the ratio of land lease revenues to budgetary revenues, we can get a sense

of how important land transfer income is to local governments and thus how hard

local governments have pushed for property market development. As shown in Table

1, the ratio of land lease revenues to budgetary fiscal income is as high as 23.75% on

average, and the maximum ratio in our sample amounts to 170.47%. This shows the

importance of land transfer income to local governments. According to Hypothesis 2,

we expect that the estimated coefficients of real estate development strategy are

negative in Equations (1) , (3), (4) and (7), and positive in Equations (2), (5) and (6).

Real GDP per capita (GDPPC ) captures the stage of economic development of

different provinces. It is derived from the data on nominal GDP per capita and the

GDP deflator. To incorporate the potential nonlinear relationship (U-shaped and

inverted U-shaped relations), we include both real GDP per capita and its square term

(GDPPC-sq.).

The old-age dependency ratio (Old Age Dependency Ratio) is measured as the

ratio of the number of people aged 65 and over to the number of people aged 15-64 in

29

a province (National Bureau of Statistics, 2009). To allow for the possible U-shaped

and inverted-U-shaped relationship, we include both the aged dependency ratio and its

squared term (Odr2).

Besides, we also include two additional control variables in regression analysis,

that is, economic openness and private economy development. The variable of

economic openness is defined as the sum of exports and imports divided by GDP. The

variable of private economy development is defined as the ratio of industrial

production value of the non-state sector in the total industrial value (Bai et al.,2004).

Economic openness may affect the bargaining power of owners of different types of

factors and is expected to raise capital share and lower labor share (Harrison, 2002;

Guscina, 2006). After examining over 100 countries over the period 1960-1997,

Harrison (2002) finds that economic openness is negatively related to labor share in

income. She argues that this is because of the stronger bargaining power of capital

than that of labor in a financially-integrated world. Guscina (2006) argues that this

“bargaining power” mechanism also plays an important role in generating the

negative impacts of economic openness on labor share in industrialized countries.

However, Diwan (2000, 2001) notes that the impact of economic openness on labor

share varies from country to country, and that results are highly sensitive to the way of

modeling. Theoretically, the impacts of private economy development on income

shares are ambiguous. On the one hand, private economy could lower labor income

share. Azmat et al. (2011) find that privatization has been an important factor in the

fall of labor’s share of value added over the past two decades in the network

30

industries in OECD countries. They argue that this occurs because publicly-owned

firms have more preference for employment over profits than do privatized firms.

This could apply to China in economic transition. Similarly, private economy

development in China in the absence of labor rights protection might enhance the

bargaining power of capital vis-à-vis labor so as to lower labor income share. On the

other hand, the private sector in China is more likely to be engaged in labor-intensive

industries than does the state sector. Largely denied access to the state-dominated

financial system and other government favorable policies, the private sector firms find

it difficult to enter capital and technology-intensive industries having a higher

threshold requirement for capital. They are often forced to engage in labor-intensive

industries. Consequently, private economy development could boost labor income

share.

4. Empirical Results

4.1. Government Development Strategies and the consumption-investment

structure in China

In Tables 4-6, we present the regression results of the impacts of government

development strategies on the consumption-investment structure, i.e., results for

models (1) ,(2) and (3), where we use the three different indicators of the overtaking

strategy respectively. We have important findings as follows.

First, a more intensive pursuit of the overtaking strategy and the real estate

development strategy is associated with a higher fraction of investment in GDP and a

lower fration of consumption in GDP, and therefore a lower ratio of consumption to

31

investment, i.e., a more imbalanced consumption-investment structure. This is fully

consistent with the predictions of Hypotheses 1-2.

Second, consistent with Hypothesis 3, household consumption ratio, investment

ratio and ratio of consumption to investment exhibit a U-shaped, an inverted-U

shaped and U-shaped relationship with real GDP per capita respectively. When the

annual real GDP per capita is smaller (larger) than RMB 17405.1, household

consumption ratio decreases (increases) with real GDP per capita. If we look at the

data, we find that most provinces of China still lie in the left part of the U-shaped

curve with consumption ratio declining with real GDP per capita. When the annual

average real GDP per capita is smaller (larger) than RMB 19858.2, investment ratio

increases (decreases) with real GDP per capita. Similarly, we find that most of

provinces in China still lie in the left area of the inverted U-shaped curve.

Third, household consumption ratio, investment ratio and ratio of consumption to

investment exhibit a U-shaped, an inverted-U shaped and U-shaped relationship with

the aged dependency ratio respectively, which is consistent with Hypothesis 4. When

the aged dependency ratio remains below (above) 14%, household consumption ratio

would decrease (increase) in the aged dependency ratio. An examination of the data

tells us that most provinces of China still lie in the left part of the U curve with

consumption decreasing in the aged dependency ratio. Investment ratio exhibits an

opposite pattern. When the aged dependency ratio is smaller (larger) than 14.1%,

investment ratio would increase (decrease) in the aged dependency ratio. Similarly,

we find that most provinces of China still lie in the upward movement part where

32

investment rising with aged dependency ratio.

Private economy development does not have robust significant effects on

consumption ratio and the ratio of consumption to investment, but has significant

positive effects on investment ratio. Economic openness does not have robust

significant positive effects on consumption ratio and ratio of consumption to

investment, but has basically significant negative effects on investment ratio.

4.2. Government Development Strategies and the Biased Factor Income

Distribution Structure

To see how the Chinese political and economic governance system shapes the

consumption-investment structure, we analyze how the overtaking strategy, real estate

development strategy, etc. affect the structure of factor income distribution,

particularly the relative shares of labor vis-à-vis capital and government in national

income.

Tables 7-9 present the results on the effects of the overtaking strategy, real estate

development strategy, etc. on labor share, capital share and government share in the

primary income distribution. Some observations can be made. First, a more intensive

pursuit of the overtaking strategy and the real estate development strategy is

associated with a lower proportion of labor income in GDP and a higher proportion of

capital income and government income in GDP, and therefore a lower ratio of labor

income to the sum of capital and government income, i.e., a more biased primary

income distribution structure. Most of the estimated coefficients are statistically

significant. These findings are fully consistent with Hypotheses 1-2.

33

Second, as predicted by Hypothesis 3, the labor share in GDP, the capital and

governmental shares in GDP and the ratio of labor income to capital and government

income displays a U-shaped, an inverted-U shaped, an inverted-U shaped and U-

shaped relationship with real GDP per capita.

Private economy development has significant negative effects on labor share,

which is consistent with the results of Luo and Zhang (2010). As pointed out by Li et

al. (2009), economic transition increases capital owners’ bargaining power, resulting

in a decline in the labor income share. Besides, with the reforms, redundant workers

and the surplus rural labor forces enter the labor market, increase labor supply, and,

thus, exert downward pressures on wages (Luo and Zhang, 2010). Economic openness

has significant positive effects on labor income share, which is not consistent with the

results of Luo and Zhang (2010).

Furthermore, when we use the post-redistribution shares of labor income, capital

income and government income as the dependent variable respectively, we also obtain

similar results. It is not surprising at all since as shown in Figures 4-6 there is a strong

positive relationship between the primary and secondary income distribution

structure.

4.3. Income Structure as Channels

So far we have shown that government development strategies have shaped the

primary and secondary income distribution structure and the consumption-investment

structure. We now turn to test whether the impacts of development strategies upon the

consumption-investment structure work through the channel of the income

34

distribution structure. Tables 10-12 present the results of channel tests. We first

present the results of the regressions of the ratio of consumption to investment on the

two types of government development strategy proxy variables without including the

primary income distribution structure indicators. Clearly, both strategies produce

statistically significant and negative impacts on the consumption-investment ratio.

Then, we add into regressions (Column 2 of the tables) the indicator of primary

income distribution structure, i.e., the ratio of labor income to the sum of capital and

government income. We find that the primary income distribution structure variable

generates a statistically significant and positive estimated coefficient, whereas the

estimated coefficients of the two government strategy proxy variables remain

statistically significant, and that of the overtaking strategy drops slightly in

magnitude. This indicates that the primary income distribution structure serves as one

important mediating channel for the impact of government strategies on the

consumption-investment structure, but it is hardly the primary channel. Finally, in

column 3 of the tables, we implement the instrumental variable regression to deal with

the potential concern of endogeneity of the primary income distribution structure. For

example, theoretically, it could be the case that the campaign for investment by

government distorts the consumption-investment structure, and raises the share of

capital and government income and lowers that of labor income. To tackle this issue,

we use the one-year lagged value of the primary income distribution structure

indicator as an instrumental variable and conduct the two-stage fixed effects

regressions on the panel dataset. Our results remain qualitatively equivalent. The

35

estimated coefficient of the income distribution structure variable becomes larger in

magnitude, while that of the overtaking strategy indicator becomes smaller in

magnitude. Compared with the results in Column 2 in the tables, the role of the

primary income distribution structure as a channel to mediate the impacts of the

overtaking strategy on the consumption-investment structure has increased after we

conduct the instrumental variable regressions.

Furthermore, when we test whether the impacts of development strategies upon

the consumption-investment structure work through the channel of secondary income

distribution structure, we also obtain similar results. It suggests that the overtaking

strategy and the real estate development strategy have played an important part in

shaping the unbalanced consumption-investment structure. A significant part of the

impacts is mediated by the distorted primary and secondary income distribution

structure. In addition, Tables 10-12 also show that the overtaking strategy and real

estate development strategy indicators remain statistically significant after including

the primary income distribution structure indicator. This “residual significance”

suggests that the “growth-first” development strategy has also contributed to the

biased consumption-investment structure through other channels. For instance, the

real estate development strategy has stimulated speculative investment demand

through expectations of surging property prices, strengthened households’ motive for

precautionary savings, and generated huge land lease revenues, while the overtaking

strategy has weakened the social safety net for local residents and intensified

households’ motive for precautionary savings , all of which raise investment and

36

lower consumption.

Our results suggest that getting primary and secondary income distribution

structure right is not enough to achieving a consumption-based growth model in

China and Chinese government should reform its political and economic governance

system to motivate local governments to spend their fiscal resources on the

construction of social safety net.

5. Conclusion

In this paper, we develop a coherent framework for understanding the

unbalanced consumption-investment structure in China. We argue that the

fundamental cause of the imbalance between consumption and investment in China is

China’s political and economic governance system, an institutional structure that is

credited for China’s rapid economic development in the past three decades. The

overtaking strategy and the real estate development strategy generated by this

governance system contributed tremendously to China’s neck breaking economic

growth, but at the same time they led to distorted income distribution structure and

internal and external macroeconomic imbalances.

Using the overtaking strategy and the real estate development strategy to

characterize the behavior of local governments under the regionally decentralized

authoritarian system, we document a strong relationship between the two strategies

and the imbalanced consumption-investment structure. The impacts of the governance

system and its strategies remain on track even after considering the effects of

economic structure and demographic structure transformation. Moreover, we verify

37

that the biased primary and secondary income distribution structure serves as an

important mediating channel through which the governance system and its

development strategies translate into an imbalanced consumption-investment

structure. Our findings imply that the Chinese government will be able to accomplish

China’s transition from an investment-led growth model to a consumption-based

growth model only if it modifies China’s political and economic governance system

and thus removes the distortions in development strategies.

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45

Appendix A Data sources

The data on the primary income distribution structure is taken from Lv(2012). The

data to calculate household consumption ratio, i.e., household consumption

expenditures, GDP, are taken from China Compendium of Statistics 1949-2004 and

China Compendium of Statistics 1949-2008 . The original data to measure investment

ratio, that is, gross fixed capital formation and GDP, are from China Compendium of

Statistics 1949-2004 and China Compendium of Statistics 1949-2008 .Besides, the

data used to construct the measure TCI1(1995-2007), i.e., the data on the value added

of high-technology industry, GDP, employees in high-technology industry, and the

total employees, are from China Compendium of Statistics 1949-2008, China

Statistical Yearbook (Various years),and China Statistics Yearbook on High

Technology Industry (Various years). The number of local development zones and the

area of local development zones, are taken from Directory of Approved Development

Zones in China (2006) .The data to measure real estate development strategy are from

China Compendium of Statistics 1949-2008. The original data to measure GDPPC⑥,

i.e., GDP per capita and index of GDP per capita, are from China Compendium of

Statistics 1949-2008. The data to measure the old dependency ratio, i.e., the number

of people aged 65 and over and the number of people aged 15-64, are from China

Statistical Yearbook (Various years). Open is the sum of exports and imports divided

by GDP，which are from China Compendium of Statistics 1949-2008. Privatization

is the ratio of production value of industry produced by non-state-owned enterprises

over that of industry (Bai et al., 2004), which are from China Statistical Yearbook

(Various years).

⑥

1978 is a base year.

46

Table 1 Summary statistics

Variable Obs Mean Std. Dev. Min Max

Consumption ratio 324 40.50 7.77 25.66 69.67

Investment ratio 324 42.08 11.28 24.86 82.58

Consumption ratio/Investment ratio 324 1.04 0.38 0.39 2.17

Labor Income Share 324 49.14 7.83 32.8 69.4

Capital Income Share 324 36.51 7.30 17.2 50.5

Gov’t Income Share 324 14.35 3.02 7.6 26.6

Overtaking Strategy1 324 3.58 1.69 0.65 10.03

Overtaking Strategy2 296 2.96 0.93 0 5.14

Overtaking Strategy3 296 9.68 0.85 7.35 11.39

Real Estate Development Strategy 324 23.75 25.76 0.35 170.47

GDPPC 324 3631.11 3399.98 639 25268

Old Age Dependency Ratio 324 11.02 2.55 6.13 21.88

Open 324 32.21 41.43 3.2 176.5

Private economy development 324 44.69 20.67 10.12 88.16

Notes: Consumption ratio is household consumption ratio, which is the proportion of household consumption in

GDP. Investment ratio is investment ratio, which is the percentage of the total value of fixed capital formation in

GDP. Labor Income Share is the share of labor compensation in GDP. Capital Income Share is the share of capital

return in GDP. Gov’t Income Share is the share of net production tax in GDP. Overtaking Strategy1, Overtaking

Strategy2，Overtaking Strateg 3 refer to the overtaking strategy, which are measured by the ratio of the added value

of high-technology industry per capita to GDP per capita, the logarithm of the number of local development zones,

and the logarithm of the area of local development zones, respectively. Real Estate Development Strategy

represents real estate market development strategy, which is measured by the ratio of land lease revenues to

budgetary fiscal revenue. GDPPC is real GDP per capita. Old Age Dependency Ratio is measured as the ratio of

the number of people aged 65 and over to the number of people aged 15-64 in a province. Open is the sum of

exports and imports divided by GDP. Private economy development is the ratio of production value of industry

produced by non-state-owned enterprises over that of industry (Bai et al., 2004)

47

Table 2 Growth of development zones in China, 1984-2006

Number Area(thousand hectares)

National % Provincial % National % Provincial %

1984 9 90.00 1 10.00 18.86 96.32 0.72 3.68

1986 11 91.67 1 8.33 19.24 96.39 0.72 3.61

1987 12 92.31 1 7.69 19.26 96.40 0.72 3.60

1988 13 65.00 7 35.00 20.59 78.88 5.51 21.12

1989 16 66.67 8 33.33 29.60 81.30 6.81 18.70

1990 18 60.00 12 40.00 33.88 77.67 9.74 22.33

1991 46 69.70 20 30.30 85.10 85.29 14.68 14.71

1992 116 41.43 164 58.57 163.71 59.43 111.76 40.57

1993 130 32.10 275 67.90 180.50 48.45 192.04 51.55

1994 133 26.60 367 73.40 191.91 43.64 247.82 56.36

1995 136 25.37 400 74.63 199.32 42.46 270.06 57.54

1996 138 24.56 424 75.44 199.70 41.25 284.46 58.75

1997 139 23.56 451 76.44 201.91 40.09 301.76 59.91

1998 139 22.79 471 77.21 201.91 38.94 316.64 61.06

1999 139 22.24 486 77.76 201.91 38.14 327.50 61.86

2000 166 24.48 512 75.52 217.55 38.67 345.05 61.33

2001 173 24.06 546 75.94 224.21 37.92 366.98 62.08

2002 183 22.73 622 77.27 228.51 35.81 409.63 64.19

2003 197 22.39 683 77.61 231.94 34.03 449.61 65.97

2004 203 22.91 683 77.09 232.60 34.10 449.61 65.90

2005 222 24.53 683 75.47 236.76 34.49 449.61 65.51

2006 222 14.16 1346 85.84 236.76 23.69 762.59 76.31

Source:Lin, G(2009),pp.188.

Table 3 Structural characteristics of China’s development zones, 2006

48

No. % Area(thousand ha) %

National 222 100.00 236.76 100.00

Economic Technological Development Zone 49 22.07 62.81 26.53

Hi-tech Industrial Development Zone 53 23.87 96.35 40.70

Tax Concession Zone 15 6.76 3.97 1.67

Export Processing Zone 58 26.13 17.07 7.21

Border Economic Cooperation Zone 14 6.31 7.85 3.31

Others 33 14.86 48.71 20.57

Provincial 1346 100.00 762.59 100.00

Economic Development Zone 1231 91.46 681.93 89.42

Hi-tech Industrial Park 65 4.83 47.63 6.25

Special Industrial Park 50 3.71 33.03 4.33

Total 1568 999.35

Source: Lin, G(2009),pp.188 and authors’s calculation.

Note: Others include various development zones established for tourism, resorts, recreation, logistics, finance,

trading and industrial developments.

49

Table 4 Growth-First Development Strategy and the Imbalance between

Consumption and Investment

Dependent Consumption

ratio

Investment

ratio

Consumption ratio /

Investment ratio (1) (2) (3)

Overtaking Strategy1 -0.55** 1.49*** -0.07***

（0.015） （0.001） （0.000）

Real Estate Development Strategy -0.01** 0.07*** -0.002***

（0.016） （0.000） （0.003）

GDPPC -0.0022*** 0.0028*** -0.0001***

（0.000） （0.000） （0.000）

GDPPC_sq 6.32e-8 *** -7.05e-8*** 3.06e-9 ***

（0.000） （0.000） （0.000）

Old Age Dependency Ratio -2.79** 5.62*** -0.16**

（0.014） （0.007） （0.014）

Old Age Dependency Ratio-sq 0.10** -0.20*** 0.005**

（0.016） （0.007） （0.021）

Private Economy Development

-0.03

0.25***

-0.004**

(0.190) (0.000) (0.028)

Open 0.05 -0.17*** 0.005***

(0.198) (0.003) (0.006)

Intercept 67.74*** -15.24 2.87***

(0.000) （0.244） (0.000)

N 324 324 324

R2 0.5527 0.6624 0.6876

Notes: Consumption ratio is household consumption ratio, which is the proportion of household consumption in GDP.

Investment ratio is investment ratio, which is the percentage of the total value of fixed capital formation in GDP.

Overtaking Strategy1 is measured by the ratio of the added value of high-technology industry per capita to GDP per

capita. Real Estate Development Strategy is measured by the ratio of land lease revenues to budgetary fiscal revenue.

GDPPC and GDPPC_sq are real GDP per capita and its square term. Old Age Dependency Ratio and Old Age

Dependency Ratio-sq are measured as the ratio of the number of people aged 65 and over to the number of people aged

15-64 in a province and its square term. Private economy development is the ratio of production value of industry

produced by non-state-owned enterprises over that of industry (Bai et al., 2004). Open is the sum of exports and imports

divided by GDP. P values are in parentheses. *, **, *** indicate significance at 10%, 5%, and 1% level, respectively.

50

Table 5 Growth-First Development Strategy and the Imbalance between

Consumption and Investment

Dependent Consumption

ratio

Investment

ratio

Consumption ratio /

Investment ratio (1) (2) (3)

Overtaking Strategy2 -0.95 5.04* -0.13*

（0.208） （0.098） （0.107）

Real Estate Development

Strategy

-0.01** 0.06*** -0.002***

（0.015） （0.000） （0.006）

GDPPC -0.002*** 0.002*** -0.0001***

（0.000） （0.038） （0.000）

GDPPC_sq 7.59e-8 *** -8.51e-8*** 3.98e-9 ***

（0.000） （0.000） （0.000）

Old Age Dependency Ratio -2.91** 5.89** -0.20**

（0.024） （0.012） （0.029）

Old Age Dependency Ratio-sq 0.10** -0.20*** 0.006**

（0.025） （0.010） （0.031）

Private Economy Development

0.002

0.18**

-0.002

(0.949) (0.017) (0.559)

Open 0.04 -0.12 0.004

(0.536) (0.206) (0.209)

Intercept 68.62*** -23.71 3.21***

(0.000) （0.132） (0.000)

N 296 296 296

R2 0.4821 0.6493 0.6190

Notes: Consumption ratio is household consumption ratio, which is the proportion of household consumption in

GDP. Investment ratio is investment ratio, which is the percentage of the total value of fixed capital formation in GDP.

Overtaking Strategy2 is measured by the logarithm of the number of local development zones. Real Estate Development

Strategy is measured by the ratio of land lease revenues to budgetary fiscal revenue. GDPPC and GDPPC_sq are real

GDP per capita and its square term. Old Age Dependency Ratio and Old Age Dependency Ratio-sq are measured as the

ratio of the number of people aged 65 and over to the number of people aged 15-64 in a province and its square term.

Private economy development is the ratio of production value of industry produced by non-state-owned enterprises over

that of industry (Bai et al., 2004). Open is the sum of exports and imports divided by GDP. P values are in parentheses.

*, **, *** indicate significance at 10%, 5%, and 1% level, respectively.

51

Table 6 Growth-First Development Strategy and the Imbalance between

Consumption and Investment

Dependent Consumption

ratio

Investment

ratio

Consumption ratio /

Investment ratio (1) (2) (3)

Overtaking Strategy3 -2.54*** 8.25*** -0.24***

（0.001） （0.000） （0.000）

Real Estate Development Strategy -0.01*** 0.06*** -0.002***

（0.007） （0.000） （0.003）

GDPPC -0.002*** 0.002*** -0.0001***

（0.000） （0.002） （0.000）

GDPPC_sq 7.39e-8 *** -8.58e-8*** 3.94e-9 ***

（0.000） （0.000） （0.000）

Old Age Dependency Ratio -2.35** 4.67** -0.16**

（0.030） （0.015） （0.039）

Old Age Dependency Ratio-sq 0.08** -0.16** 0.005**

（0.030） （0.011） （0.044）

Private Economy Development

0.009

0.17***

-0.001

(0.732) (0.007) (0.622)

Open 0.03 -0.12* 0.004

(0.527) (0.054) (0.104)

Intercept 86.00*** -80.20*** 4.85***

(0.000) （0.001） (0.000)

N 296 296 296

R2 0.4980 0.6811 0.6431

Notes: Consumption ratio is household consumption ratio, which is the proportion of household consumption in

GDP. Investment ratio is investment ratio, which is the percentage of the total value of fixed capital formation in GDP.

Overtaking Strategy1 is measured by the logarithm of the area of local development zones. Real Estate Development

Strategy is measured by the ratio of land lease revenues to budgetary fiscal revenue. GDPPC and GDPPC_sq are real

GDP per capita and its square term. Old Age Dependency Ratio and Old Age Dependency Ratio-sq are measured as the

ratio of the number of people aged 65 and over to the number of people aged 15-64 in a province and its square term.

Private economy development is the ratio of production value of industry produced by non-state-owned enterprises over

that of industry (Bai et al., 2004). Open is the sum of exports and imports divided by GDP. P values are in parentheses.

*, **, *** indicate significance at 10%, 5%, and 1% level, respectively.

52

Table 7 Growth-First Development Strategy and Biased income distribution structure

Dependent

Labor Income

Share

Capital Income

Share

Gov’t Income

Share

Labor Income Share /(Capital Income

Share + Gov’t Income Share)

(1) (2) (3) (4)

Overtaking Strategy1 -1.47*** 1.35*** 0.12 -0.08***

(0.000) (0.000) (0.300) (0.000)

Real Estate Development Strategy

-0.03*** 0.02 0.01* -0.001***

(0.002) (0.134) (0.102) (0.001)

GDPPC -0.0019*** 0.001*** 0.0007*** -0.00006***

(0.000) (0.000) (0.002) (0.000)

GDPPC_sq 3.6e-8*** -7.69e-9 -2.83e-8** 9.25e-10 ***

(0.001) (0.164) (0.034) (0.000)

Private Economy

Development

-0.05**

0.09***

-0.04** -0.004***

(0.044) (0.000) (0.048) (0.005)

Open 0.12*** -0.10*** -0.01** 0.005***

(0.000) (0.000) (0.030) (0.000)

Intercept 59.92*** 26.35*** 13.74*** 1.56***

(0.000) (0.000) (0.000) (0.000)

N 324 324 324

324

R2 0.4045 0.2975 0.1094 0.4213

Notes: Labor Income Share is the share of labor compensation in GDP. Capital Income Share is the share of capital return in GDP. Gov’t

Income Share is the share of net production tax in GDP. Overtaking Strategy1 is measured by the ratio of the added value of high-

technology industry per capita to GDP per capita. Real Estate Development Strategy is measured by the ratio of land lease revenues to

budgetary fiscal revenue. GDPPC and GDPPC_sq are real GDP per capita and its square term. Private economy development is the ratio of

production value of industry produced by non-state-owned enterprises over that of industry (Bai et al., 2004). Open is the sum of exports

and imports divided by GDP. P values are in parentheses. *, **, *** indicate significance at 10%, 5%, and 1% level, respectively.

53

Table 8 Growth-First Development Strategy and Biased income distribution structure

Dependent

Labor Income

Share

Capital Income

Share

Gov’t Income

Share

Labor Income Share

/(Capital Income Share +

Gov’t Income Share)

(1) (2) (3) (4)

Overtaking Strategy2 -2.69 1.85 0.84 -0.16

(0.231) (0.217) (0.329) (0.148)

Real Estate

Development Strategy

-0.05*** 0.04*** 0.01* -0.002***

(0.000) (0.001) (0.096) (0.000)

GDPPC -0.002*** 0.002*** 0.0007*** -0.00007***

(0.000) (0.002) (0.000) (0.003)

GDPPC_sq 4.99e-8*** -6.27e-9 -4.36e-8*** 1.40e-9 ***

(0.001) (0.164) (0.002) (0.000)

Private Economy

Development

-0.02

0.07**

-0.05** -0.002

(0.635) (0.014) (0.025) (0.450)

Open 0.13*** -0.14*** 0.007 0.007***

(0.010) (0.001) (0.544) (0.003)

Intercept 61.57*** 26.52*** 11.91*** 1.65***

(0.000) (0.001) (0.000) (0.000)

N 296

296

296

296

R2 0.3270 0.2172 0.1289

0.3101

Notes: Labor Income Share is the share of labor compensation in GDP. Capital Income Share is the share of capital return in GDP. Gov’t

Income Share is the share of net production tax in GDP. Overtaking Strategy2 is measured by the logarithm of the number of local

development zones. Real Estate Development Strategy is measured by the ratio of land lease revenues to budgetary fiscal revenue. GDPPC

and GDPPC_sq are real GDP per capita and its square term. Private economy development is the ratio of production value of industry

produced by non-state-owned enterprises over that of industry (Bai et al., 2004). Open is the sum of exports and imports divided by GDP.

P values are in parentheses. *, **, *** indicate significance at 10%, 5%, and 1% level, respectively.

54

Table 9 Growth-First Development Strategy and Biased income distribution structure

Dependent

Labor Income

Share

Capital Income

Share

Gov’t Income

Share

Labor Income Share

/(Capital Income Share +

Gov’t Income Share)

(1) (2) (3) (4)

Overtaking Strategy3 -4.10** 3.02*** 1.07 -0.23***

(0.022) (0.003) (0.214) (0.009)

Real Estate

Development Strategy

-0.05*** 0.03*** 0.01* -0.002***

(0.000) (0.002) (0.108) (0.000)

GDPPC -0.002*** 0.001*** 0.0007*** -0.00008***

(0.000) (0.000) (0.002) (0.000)

GDPPC_sq 4.84e-8*** -4.44e-9 -4.39e-8*** 1.38e-9 ***

(0.003) (0.336) (0.002) (0.002)

Private Economy

Development

-0.01

0.06***

-0.05** -0.001

(0.740) (0.005) (0.033) (0.471)

Open 0.13*** -0.14*** 0.007 0.006***

(0.000) (0.000) (0.439) (0.000)

Intercept 92.92*** 3.12*** 3.96 3.35***

(0.000) (0.728) (0.630) (0.000)

N 296 296 296

296

R2 0.3442 0.2288 0.1315 0.3295

Notes: Labor Income Share is the share of labor compensation in GDP. Capital Income Share is the share of capital return in GDP. Gov’t

Income Share is the share of net production tax in GDP. Overtaking Strategy3 is measured by the logarithm of the area of local development

zones. Real Estate Development Strategy is measured by the ratio of land lease revenues to budgetary fiscal revenue. GDPPC and

GDPPC_sq are real GDP per capita and its square term. Private economy development is the ratio of production value of industry produced

by non-state-owned enterprises over that of industry (Bai et al., 2004). Open is the sum of exports and imports divided by GDP. P values

are in parentheses. *, **, *** indicate significance at 10%, 5%, and 1% level, respectively.

55

Table 10 Growth-First Development Strategy and the Imbalance between Consumption and

Investment: Channel test

Dependent

Consumption ratio /

Investment ratio

Consumption ratio /

Investment ratio

Consumption ratio /

Investment ratio

(1) (2) (3)

Labor Income Share /

(Capital Income Share + Gov’t Income

Share)

0.13* 0.21**

（0.067） （0.017）

Overtaking Strategy1 -0.07*** -0.06*** -0.04***

（0.000） （0.000） （0.002）

Real Estate Development Strategy -0.002*** -0.002*** -0.002***

（0.003） （0.009） （0.006）

GDPPC -0.0001*** -0.0001*** -0.0001***

（0.000） （0.000） （0.000）

GDPPC_sq 3.06e-9 *** 2.97e-9*** 2.95e-9***

（0.000） （0.000） （0.000）

Old Age Dependency Ratio -0.16** -0.15** -0.11***

（0.014） （0.014） （0.001）

Old Age Dependency Ratio-sq 0.005** 0.005** 0.003***

（0.021） （0.023） （0.008）

Private Economy Development

-0.004**

-0.004*

-0.004**

(0.028) （0.062） （0.027）

Open 0.005*** 0.004** 0.005***

(0.006) （0.021） （0.002）

Intercept 2.87*** 2.61*** ─c

(0.000) （0.000） ─

Endogeneity test ─ ─ 0.07

Method FEa FE

a FE

b

N 324 324 297

R2 0.6876 0.6947 0.6841

Notes: Consumption ratio is household consumption ratio, which is the proportion of household consumption in GDP. Investment

ratio is investment ratio, which is the percentage of the total value of fixed capital formation in GDP. Labor Income Share is the share

of labor compensation in GDP. Capital Income Share is the share of capital return in GDP. Gov’t Income Share is the share of net

production tax in GDP. Overtaking Strategy1 is measured by the ratio of the added value of high-technology industry per capita to

GDP per capita. Real Estate Development Strategy represents real estate market development strategy, which is measured by the ratio

of land lease revenues to budgetary fiscal revenue. GDPPC is real GDP per capita. Old Age Dependency Ratio and Old Age

Dependency Ratio-sq are measured as the ratio of the number of people aged 65 and over to the number of people aged 15-64 in a

province and its square term. Open is the sum of exports and imports divided by GDP. Private economy development is the ratio of

production value of industry produced by non-state-owned enterprises over that of industry (Bai et al., 2004)

P values are in parentheses. *, **, *** indicate significance at 10%, 5%, and 1% level, respectively.

a: Method proposed by Driscoll and Kraay is used.

b: We lag Laborshare/(Capshare+Govershare) by one year as instrument variables

c: We use xtivreg2 Command to estimate this model.

56

Table 11 Growth-First Development Strategy and the Imbalance between Consumption and

Investment: Channel test

Dependent

Consumption ratio /

Investment ratio

Consumption ratio /

Investment ratio

Consumption ratio /

Investment ratio

(1) (2) (3)

Labor Income Share /

(Capital Income Share + Gov’t Income

Share)

0.20** 0.29***

（0.014） （0.002）

Overtaking Strategy2 -0.13* -0.11* -0.07*

（0.107） （0.074） （0.073）

Real Estate Development Strategy -0.002*** -0.002** -0.002**

（0.006） （0.020） （0.017）

GDPPC -0.0001*** -0.0001*** -0.0001***

（0.000） （0.000） （0.000）

GDPPC_sq 3.98e-9 *** 3.81e-9*** 3.70e-9***

（0.000） （0.000） （0.000）

Old Age Dependency Ratio -0.20** -0.18** -0.11***

（0.029） （0.026） （0.003）

Old Age Dependency Ratio-sq 0.006** 0.006** 0.003***

（0.031） （0.031） （0.010）

Private Economy Development

-0.002

-0.001

-0.002

(0.559) （0.637） （0.394）

Open 0.004 0.003 0.004**

(0.209) （0.308） （0.035）

Intercept 3.21*** 2.72*** ─c

(0.000) （0.000） ─

Endogeneity test ─ ─ 0.05

Method FEa FE

a FE

b

N 296 296 270

R2 0.6190 0.6404 0.6371

Notes: Consumption ratio is household consumption ratio, which is the proportion of household consumption in GDP. Investment

ratio is investment ratio, which is the percentage of the total value of fixed capital formation in GDP. Labor Income Share is the share

of labor compensation in GDP. Capital Income Share is the share of capital return in GDP. Gov’t Income Share is the share of net

production tax in GDP. Overtaking Strategy2 is measured by the logarithm of the number of local development zones. Real Estate

Development Strategy represents real estate market development strategy, which is measured by the ratio of land lease revenues to

budgetary fiscal revenue. GDPPC is real GDP per capita. Old Age Dependency Ratio and Old Age Dependency Ratio-sq are measured

as the ratio of the number of people aged 65 and over to the number of people aged 15-64 in a province and its square term. Open is

the sum of exports and imports divided by GDP. Private economy development is the ratio of production value of industry produced by

non-state-owned enterprises over that of industry (Bai et al., 2004). P values are in parentheses. *, **, *** indicate significance at 10%,

5%, and 1% level, respectively.

a: Method proposed by Driscoll and Kraay is used.

b: We lag Laborshare/(Capshare+Govershare) by one year as instrument variables

c: We use xtivreg2 Command to estimate this model.

57

Table 12 Growth-First Development Strategy and the Imbalance between Consumption and

Investment: Channel test

Dependent

Consumption ratio /

Investment ratio

Consumption ratio /

Investment ratio

Consumption ratio /

Investment ratio

(1) (2) (3)

Labor Income Share /

(Capital Income Share + Gov’t Income

Share)

0.18** 0.26***

（0.024） （0.006）

Overtaking Strategy3 -0.24*** -0.21*** -0.16***

（0.000） （0.000） （0.002）

Real Estate Development Strategy -0.002*** -0.002** -0.002**

（0.003） （0.011） （0.013）

GDPPC -0.0001*** -0.0001*** -0.0001***

（0.000） （0.000） （0.000）

GDPPC_sq 3.94e-9 *** 3.78e-9*** 3.70e-9***

（0.000） （0.000） （0.000）

Old Age Dependency Ratio -0.16** -0.15** -0.09**

（0.039） （0.036） （0.017）

Old Age Dependency Ratio-sq 0.005** 0.004** 0.003**

（0.044） （0.044） （0.048）

Private Economy Development

-0.001

-0.0009

-0.001**

(0.622) （0.703） （0.489）

Open 0.004 0.003** 0.004**

(0.104) （0.206） （0.028）

Intercept 4.85*** 4.22*** ─c

(0.000) （0.000） ─

Endogeneity test ─ ─ 0.06

Method FEa FE

a FE

b

N 296 296 270

R2 0.6431 0.6590 0.6542

Notes: Consumption ratio is household consumption ratio, which is the proportion of household consumption in GDP. Investment

ratio is investment ratio, which is the percentage of the total value of fixed capital formation in GDP. Labor Income Share is the share

of labor compensation in GDP. Capital Income Share is the share of capital return in GDP. Gov’t Income Share is the share of net

production tax in GDP. Overtaking Strategy3 is measured by the logarithm of the area of local development zones. Real Estate

Development Strategy represents real estate market development strategy, which is measured by the ratio of land lease revenues to

budgetary fiscal revenue. GDPPC is real GDP per capita. Old Age Dependency Ratio and Old Age Dependency Ratio-sq are measured

as the ratio of the number of people aged 65 and over to the number of people aged 15-64 in a province and its square term. Open is

the sum of exports and imports divided by GDP. Private economy development is the ratio of production value of industry produced by

non-state-owned enterprises over that of industry (Bai et al., 2004). P values are in parentheses. *, **, *** indicate significance at 10%,

5%, and 1% level, respectively.

a: Method proposed by Driscoll and Kraay is used.

b: We lag Laborshare/(Capshare+Govershare) by one year as instrument variables

c: We use xtivreg2 Command to estimate this model.

58

Figure 1 The evolution of ratio of assets of heavy industry to total assets of

industry in China

Notes: (1) Industry includes heavy industry and light industry; (2) data sources:China Industrial

Economic Statistical Yearbook (various years) and China Statistical Yearbook (various years)

Figure 2 The evolution of ratio of value added of heavy industry to total value

added of industry in China

Notes:(1)Industry includes heavy industry and light industry;(2) Figure 4 reveals why Chinese

local governments developed capital and technology-intensive heavy industry rather than labor-

intensive light industry; (3) data sources: China Industrial Economic Statistical Yearbook (various

years) and China Statistical Yearbook (various years)

58

60

62

64

66

68

70

72

74

76

78

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

54

56

58

60

62

64

66

68

70

72

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007

59

Figure 3 The evolution of ratio of tax payable of heavy industry to total tax

payable of industry, and ratio of value added tax payable of heavy industry to

total value added tax payable of industry in China

Notes:(1) Manufacturing industries are classified into heavy industry and light industry;(2) tax

payable equals the sum of value added tax payable and taxes and other charges on principal

business revenues; (3) Figure 6 shows why Chinese local governments developed capital and

technology-intensive heavy industry rather than labor-intensive light industry. If taking enterprise

income tax in the secondary income distribution into account, our result will be reinforced; (4)

data sources:China Industrial Economic Statistical Yearbook (various years) and China Statistical

Yearbook (various years).

Figure 4 Labor Income Share and After-redistribution Labor Income Share

Data source:Lv and Guo(2012).

50

55

60

65

70

75

1994 1995 1996 1997 1998 1999 2000 2001 2002 2003 2004 2005 2006 2007 2008 2009

Ratio of tax payable of heavy industry Ratio of value added tax payable of heavy industry

3040

5060

70

30 40 50 60 70Labor Income Share

After-redistribution Labor Income Share Fitted values

60

Figure 5 Capital Income Share and After-redistribution Capital Income Share

Data source:Lv and Guo(2012).

Figure 6 Government Income Share and After-redistribution Government

Income Share

Data source:Lv and Guo(2012).

1020

3040

50

20 30 40 50Capital Income Share

After-redistribution Capital Income Share Fitted values

1020

3040

5 10 15 20 25Government Income Share

After-redistribution Government Income Share Fitted values